Creating Confidence Intervals for Machine Learning Classifiers
Read OriginalThis technical article explains various methods for creating confidence intervals to evaluate machine learning classifier performance. It covers normal approximation intervals, multiple bootstrapping techniques, and intervals from retraining with different random seeds, providing practical approaches to quantify uncertainty in model accuracy metrics.
Comments
No comments yet
Be the first to share your thoughts!
Browser Extension
Get instant access to AllDevBlogs from your browser
Top of the Week
1
React vs Browser APIs (Mental Model)
Jivbcoop
•
3 votes
2
3
Building Type-Safe Compound Components
TkDodo Dominik Dorfmeister
•
2 votes
4
Using Browser Apis In React Practical Guide
Jivbcoop
•
1 votes
5
Better react-hook-form Smart Form Components
Maarten Hus
•
1 votes